Creating a highly accurate pronunciation dictionary plays an important role in building English TTS system to produce high quality synthesised speech. Majority of the existing studies related to building Indian English TTS systems adapt CMU pronunciation dictionary to corresponding target Indian accent. Majority of these studies use hand-crafted rule-based approaches to adapt to the target language. Creating such rules requires deep understanding of the target language and it is time-consuming. For low resource languages, creating such resources may not be a trivial task. This paper addresses this issue by transforming the problem into a sequential labelling problem. The effectiveness of three state-of-art sequential labelling methods namely CRF, MEMM and HMM are investigated for Manipuri language (one of the low resource scheduled Indian languages). From various experimental results, it is evident that CRF can effectively generate Manipuri accented English pronunciation dictionary.